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» Association rules mining using heavy itemsets
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KDD
1997
ACM
154views Data Mining» more  KDD 1997»
14 years 1 months ago
Autonomous Discovery of Reliable Exception Rules
This paper presents an autonomous algorithm for discovering exception rules from data sets. An exception rule, which is defined as a deviational pattern to a well-known fact, exhi...
Einoshin Suzuki
BTW
1999
Springer
145views Database» more  BTW 1999»
14 years 2 months ago
A Multi-Tier Architecture for High-Performance Data Mining
Data mining has been recognised as an essential element of decision support, which has increasingly become a focus of the database industry. Like all computationally expensive data...
Ralf Rantzau, Holger Schwarz
HICSS
2005
IEEE
164views Biometrics» more  HICSS 2005»
14 years 3 months ago
An Efficient Technique for Frequent Pattern Mining in Real-Time Business Applications
Association rule mining in real-time is of increasing thrust in many business applications. Applications such as e-commerce, recommender systems, supply-chain management and group...
Rajanish Dass, Ambuj Mahanti
DIS
2003
Springer
14 years 3 months ago
Extraction of Coverings as Monotone DNF Formulas
Abstract. In this paper, we extend monotone monomials as large itemsets in association rule mining to monotone DNF formulas. First, we introduce not only the minimum support but al...
Kouichi Hirata, Ryosuke Nagazumi, Masateru Harao
IISWC
2006
IEEE
14 years 3 months ago
MineBench: A Benchmark Suite for Data Mining Workloads
Abstract— Data mining constitutes an important class of scientific and commercial applications. Recent advances in data extraction techniques have created vast data sets, which ...
Ramanathan Narayanan, Berkin Özisikyilmaz, Jo...